library(tidyverse)
library(whereiation)
df <- msleep %>% select(-awake)
dep_var <- 'sleep_total > 12'
# df <- mpg
# dep_var <- "hwy > 25"
variation_plot_interactive(df, dep_var)
variation_plot_single_obs(df, dep_var, id = 72) #%>% plotly::ggplotly(tooltip = "label")
profile_n(df, dep_var)
| field | field_wt |
ID 40 est: 0.6345 |
ID 72 est: 0.6052 |
ID 16 est: 0.5897 |
ID 43 est: 0.5866 |
ID 73 est: 0.5866 |
|---|---|---|---|---|---|---|
| sleep_rem | 24% |
05 [2.7 to 3.35) 0.667 |
05 [2.7 to 3.35) 0.667 |
03 [1.4 to 2.05) 0.6 |
03 [1.4 to 2.05) 0.6 |
03 [1.4 to 2.05) 0.6 |
| order | 24% |
Rodentia 0.636 |
Rodentia 0.636 |
Rodentia 0.636 |
small sample size | small sample size |
| conservation | 9% | small sample size |
lc 0.444 |
small sample size | small sample size | small sample size |
| vore | 3% |
herbi 0.438 |
herbi 0.438 |
omni 0.2 |
small sample size | small sample size |
| brainwt | 0% |
01 [-0.00 to 0.57) 0.346 |
NA NA 0.481 |
01 [-0.00 to 0.57) 0.346 |
01 [-0.00 to 0.57) 0.346 |
01 [-0.00 to 0.57) 0.346 |
| sleep_cycle | 0% |
01 [0.11 to 0.25) 0.643 |
NA NA 0.353 |
NA NA 0.353 |
01 [0.11 to 0.25) 0.643 |
01 [0.11 to 0.25) 0.643 |
find_drivers(df, dep_var)
expected_proportions(df, dep_var, sort_by = "actual")